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Introduction to the Mathematical and Statistical Foundations of Econometrics.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Introduction to the Mathematical and Statistical Foundations of Econometrics./
作者:	Bierens, Herman J.
其他作者:	Gourieroux, Christian.
出版者:	Cambridge :Cambridge University Press, : 2004.,
面頁冊數:	345 p.
標題:	Econometrics. -
電子資源:	Click here to view book
ISBN:	9780511079658 (electronic bk.)

Introduction to the Mathematical and Statistical Foundations of Econometrics.
Bierens, Herman J.

Introduction to the Mathematical and Statistical Foundations of Econometrics.[electronic resource]. - Cambridge :Cambridge University Press,2004. - 345 p.

Cover; Half-title; Series-title; Title; Copyright; Contents; Preface; 1 Probability and Measure; 2 Borel Measurability, Integration, and Mathematical Expectations; 3 Conditional Expectations; 4 Distributions and Transformations; 5 The Multivariate Normal Distribution and Its Application to Statistical Inference; 6 Modes of Convergence; 7 Dependent Laws of Large Numbers and Central Limit Theorems; 8 Maximum Likelihood Theory; Appendix I – Review of Linear Algebr; Appendix II – Miscellaneous Mathematics; Appendix III – A Brief Review of Complex Analysis; Appendix IV – Tables of Critical Values

Intended for use in a rigorous introductory PhD level course in econometrics, or a field course in econometric theory, this book covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, and more.

Electronic reproduction.

Available via World Wide Web.

Mode of access: World Wide Web.

ISBN: 9780511079658 (electronic bk.)Subjects--Topical Terms:

556981
Econometrics.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: HB139 .B527 2004eb

Dewey Class. No.: 330.015195

Introduction to the Mathematical and Statistical Foundations of Econometrics.
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505 0 $a Cover; Half-title; Series-title; Title; Copyright; Contents; Preface; 1 Probability and Measure; 2 Borel Measurability, Integration, and Mathematical Expectations; 3 Conditional Expectations; 4 Distributions and Transformations; 5 The Multivariate Normal Distribution and Its Application to Statistical Inference; 6 Modes of Convergence; 7 Dependent Laws of Large Numbers and Central Limit Theorems; 8 Maximum Likelihood Theory; Appendix I – Review of Linear Algebr; Appendix II – Miscellaneous Mathematics; Appendix III – A Brief Review of Complex Analysis; Appendix IV – Tables of Critical Values
505 8 $a ReferencesIndex
520 $a Intended for use in a rigorous introductory PhD level course in econometrics, or a field course in econometric theory, this book covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, and more.
533 $a Electronic reproduction. $n Available via World Wide Web.
538 $a Mode of access: World Wide Web.
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